To prevent students from learning risks and improve teachers' teaching quality, it is of great significance to provide accurate early warning of learning performance to students by analyzing their interactions through an e-learning system. In existing research, the correlations between learning risks and students' changing cognitive abilities or…

Learning style recognition is an indispensable part of achieving personalized learning in online learning systems. The traditional inventory method for learning style identification faces the limitations such as subject and static characteristics. Therefore, an automatic and reliable learning style recognition mechanism is designed in this…

Owing to the rapid development of information and communication technologies, online or mobile learning content is widely available on the Internet. Unlike traditional face-to-face learning, online learning exhibits a critical limitation: real-time interactions between learners and teachers are generally not feasible in online learning. To…

The metaverse is a network of interoperable and persistent 3-D virtual worlds where users can coexist and interact through mechanisms, such as gamification, nonfungible tokens, and cryptocurrencies. Although the metaverse is a theoretical construct today, many collaborative virtual reality (CVR) applications have emerged as potential components of…

Students learn not only directly from their teachers and books, but also by using their computers, tablets, and phones. Monitoring these learning environments creates new opportunities for teachers to track students' progress. In particular, this article is based on gathering real-time events as students interact with learning tools and materials…

In this article, we preliminarily discuss the limitations of current video conferencing platforms in online synchronous learning. Research has shown that while the involved technologies are appropriate for collaborative video calls, they often fail to replicate the rich nature of face-to-face interactions among students and between students and…

The Internet-of-Things (IoT) is a collection of technologies to bring the Internet to physically embedded devices and to embed them deeply into human activities to aid in a variety of activities. IoT gained traction with developers and consumers in recent years, driven by low-cost open-source hardware that enables easy prototyping and testing. IoT…

The main challenge in higher education is student retention. While many methods have been proposed to overcome this challenge, early and continuous feedback can be very effective. In this article, we propose a method for predicting student final grades in a course using only their performance data in the current semester. It assists students in…

In recent years, there has been an increasing trend of utilizing artificial intelligence (AI) methodologies over traditional statistical methods for predicting student performance in e-learning contexts. Notably, many researchers have adopted AI techniques without conducting a comprehensive investigation into the most appropriate and accurate…

With the rapid advancement of education, personalized learning has gained considerable attention in recent years. Learning path plays an important role in this area and has attracted great concern. Many generating mechanisms have been proposed from different perspectives for assisting learning. Some methods focus on learners' interest, while some…

Research into self-regulated learning has traditionally relied upon self-reported data. While there is a rich body of literature that has extracted invaluable information from such sources, it suffers from a number of shortcomings. For instance, it has been shown that surveys often provide insight into students' perceptions about learning rather…

In conventional laboratories, engineering students must attend in person to conduct experiments with real equipment in a physical place, where their work is mainly assessed through self-reports and attendance records. By comparison, online labs can record and analyze students' activities and behaviors automatically. Thus, this article proposes a…

Many educational institutions are using predictive models to leverage actionable insights using student data and drive student success. A common task has been predicting students at risk of dropping out for the necessary interventions to be made. However, issues of discrimination by these predictive models based on protected attributes of students…

The present study is related to the problem associated with student assessment with online examinations at higher educational institutes (HEIs). With the current COVID-19 outbreak, the majority of educational institutes are conducting online examinations to assess their students, where there would always be a chance that the students go for…

This research project investigates the impact of prompt engineering, a key aspect of chat generative pretrained transformer (ChatGPT), on college students' information retrieval in flipped classrooms. In recent years, an increasing number of students have been using AI-based tools, such as ChatGPT rather than traditional research engines to learn…